firecrown.likelihood.gauss_family.gaussian.ConstGaussian#

class firecrown.likelihood.gauss_family.gaussian.ConstGaussian(statistics)[source]#

A Gaussian log-likelihood with a constant covariance matrix.

Public Methods:

`compute_loglike`(tools)	Compute the log-likelihood.
`make_realization_vector`()	Create a new realization of the model.

Inherited from GaussFamily

`__init__`(statistics)	Initialize the base class parts of a GaussFamily object.
`read`(sacc_data)	Read the covariance matrix for this likelihood from the SACC file.
`get_cov`([statistic])	Gets the current covariance matrix.
`get_data_vector`()	Get the data vector from all statistics in the right order.
`compute_theory_vector`(tools)	Computes the theory vector using the current instance of pyccl.Cosmology.
`get_theory_vector`()	Get the theory vector from all statistics in the right order.
`compute`(tools)	Calculate and return both the data and theory vectors.
`compute_chisq`(tools)	Calculate and return the chi-squared for the given cosmology.
`get_sacc_indices`([statistic])	Get the SACC indices of the statistic or list of statistics.
`make_realization`(sacc_data[, add_noise, strict])	Create a new realization of the model.

Inherited from Likelihood

`__init__`([parameter_prefix])	Default initialization for a base Likelihood object.
`read`(sacc_data)	Read the covariance matrix for this likelihood from the SACC file.
`make_realization_vector`()	Create a new realization of the model.
`make_realization`(sacc_data[, add_noise, strict])	Create a new realization of the model.
`compute_loglike`(tools)	Compute the log-likelihood of generic CCL data.

Inherited from Updatable

`__init__`([parameter_prefix])	Updatable initialization.
`__setattr__`(key, value)	Set the attribute named `key` to the supplied value.
`set_parameter`(key, value)	Sets the parameter to the given value.
`set_internal_parameter`(key, value)	Assure this InternalParameter has not already been set, and then set it.
`set_sampler_parameter`(value)	Assure this SamplerParameter has not already been set, and then set it.
`update`(params)	Update self by calling to prepare for the next MCMC sample.
`is_updated`()	Determine if the object has been updated.
`reset`()	Reset the updatable.
`required_parameters`()	Returns a RequiredParameters object.
`get_derived_parameters`()	Returns a collection of derived parameters.

Private Methods:

Inherited from GaussFamily

`_update`(_)	Handle the state resetting required by `GaussFamily` likelihoods.
`_reset`()	Handle the state resetting required by `GaussFamily` likelihoods.

Inherited from Updatable

`_update`(params)	Method for auxiliary updates to be made to an updatable.
`_reset`()	Abstract method implemented by all concrete classes to update self.
`_required_parameters`()	Return a RequiredParameters object containing the information for this class.
`_get_derived_parameters`()	Returns the derived parameters of an implementation.

compute_loglike(tools)[source]#

Compute the log-likelihood.

make_realization_vector()[source]#

Create a new realization of the model.

firecrown.likelihood.gauss_family.gaussian.ConstGaussian